Back to Search Start Over

Affordable generic digital twins for existing building environment management and an onsite deployment.

Authors :
Li, Jingming
Wang, Jiaoju
Source :
Architectural Intelligence; 8/2/2024, Vol. 3 Issue 1, p1-17, 17p
Publication Year :
2024

Abstract

The energy consumption during the operation and maintenance phase of buildings is huge. As the built-up area in China increases, the demand for energy conservation in existing buildings has become a key focus of its dual carbon policy. Intelligent operation and maintenance based on digital twins is an emerging means to reduce carbon emissions from buildings, but it faces some problems in the process of promotion. Complete digital and intelligent transformation requires significant investment and has certain requirements for project parties and operation and maintenance teams. Small businesses or individual households have relatively simple requirements for intelligent operation and maintenance scenarios and do not require complete digital twins. To address the above issues, this article uses an affordable universal digital twin framework to provide a digital solution for intelligent operation and maintenance of existing buildings. This solution allows networking communication between devices and uses IoT modules to monitor and control the environment. This digital twinning model can reduce the measurement and control of energy-consuming end devices without on-site transformation and has rich scalability. This article uses the solution to deploy an office at a university in Henan Province and specifically measures the power consumption of displays, indoor environment, and air conditioning. According to the needs, it expands the space occupation, fans, air handlers, lights, and other end devices of the digital twin. The digital twin accurately presents the energy consumption of the office during extreme weather conditions, which has an auxiliary role in promoting digital twins in the region and optimizing energy consumption in existing buildings. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
27316726
Volume :
3
Issue :
1
Database :
Complementary Index
Journal :
Architectural Intelligence
Publication Type :
Academic Journal
Accession number :
178806884
Full Text :
https://doi.org/10.1007/s44223-024-00071-2